Although significant performance gains offered by IRS have been reported in the open literature, the prior of perfect CSI for all channels involved are generally assumed [1]}, [2]}, [3]}, [4]}, [5]}, [6]}, [7]}. In practice, the acquisition of accurate CSI, especially the reflection channel coefficients, is a difficult task due to the passive component at IRS as well as its large number of reflecting elements [8]}. One of the considerations is the semi-passive channel estimation by installing only a small number of sensing elements to estimate the channels of the BS-IRS link and the user-IRS link, respectively [8]}, [10]}, [11]}. During the channel estimation phase, the IRS works at the sensing mode by switching off all reflecting elements. The activated sensors receive the pilots from the BS/user and then estimate the channels associated with the sensors. Furthermore, the actual channels of the BS-IRS link and the user-IRS link are obtained by sophisticated signal processing techniques, e.g., compressed sensing, and machine learning [11]}. It is noted that the efficiency of the IRS adopting the semi-passive channel estimation approach is heavily dependent on the number of sensors, the quantization level of the analog-to-digital converter (ADC) at the sensors as well as the sensing duration [8]}.
